The trust layer for AI-driven engineering. Bugasura tells you which modules are degrading, which revenue flows are at risk, and gives every AI agent the full context of your product — so nothing ships blind.
You can't answer: which parts of my product are healthy right now, which revenue flows are at risk, and does my AI even know what my product is?
Which parts of my product are healthy? What's at risk and what does it cost? Does my AI even know what my product is? Bugasura answers all three with a system, not a guess.
A drill-down view across every module and submodule, with real-time RAG health status calculated from actual bugs and test coverage. Spot the broken parts of your product before they ship.
Define your revenue-critical and business-critical flows. Bugasura monitors them continuously, links every bug to the flow it touches, and shows you exactly what each broken path is costing in real money.
An AI-built unified knowledge base across your website, mobile app, codebase, server logs, meeting notes, designs, Jira and Asana — chat with it, and ground every AI test, bug fix, and feature in actual product reality.
When Eagle Eye flags a module or Revenue Flows shows risk, the Action Engine generates the missing tests via Testpert, prioritizes fixes by revenue impact, and lets you decide release vs hold with the full picture.
A canonical testing reference model — built from 14+ years of enterprise QA delivery, production failures across BFSI, healthtech and e-commerce, real user behavior patterns, and proven risk-based testing strategies.
Every Eagle Eye health score, every Revenue Flow definition, and every Knowledge Base inference is calibrated against this model.
At companies where AI is writing meaningful portions of code or tests.
If Cursor, Copilot, or Claude is rolled out across your engineering org — this is for you.